Offering a unifying theoretical perspective not readily available in any other text, this innovative guide to econometrics uses simple geometrical arguments to develop students' intuitive understanding of basic and advanced topics, emphasizing throughout the practical applications of modern theory and nonlinear techniques of estimation. One theme of the text is the use of artificial regressions for estimation, reference, and specification testing of nonlinear models, including diagnostic tests for parameter constancy, serial correlation, heteroscedasticity, and other types of mis-specification. Explaining how estimates can be obtained and tests can be carried out, the authors go beyond a mere algebraic description to one that can be easily translated into the commands of a standard econometric software package. Covering an unprecedented range of problems with a consistent emphasis on those that arise in applied work, this accessible and coherent guide to the most vital topics in econometrics today is indispensable for advanced students of econometrics and students of statistics interested in regression and related topics. It will also suit practising econometricians who want to update their skills. Flexibly designed to accommodate a variety of course levels, it offers both complete coverage of the basic material and separate chapters on areas of specialized interest.

Estimation and Inference in Econometrics

Misallocation and productivity

Much of the prior research on interorganizational learning has focused on the role of absorptive capacity, a firm's ability to value, assimilate, and utilize new external knowledge. However, this definition of the construct suggests that a firm has an equal capacity to learn from all other organizations. We reconceptualize the firm-level construct absorptive capacity as a learning dyad-level construct, relative absorptive capacity. One firm's ability to learn from another firm is argued to depend on the similarity of both firms' (1) knowledge bases, (2) organizational structures and compensation policies, and (3) dominant logics. We then test the model using a sample of pharmaceutical–biotechnology R&D alliances. As predicted, the similarity of the partners' basic knowledge, lower management formalization, research centralization, compensation practices, and research communities were positively related to interorganizational learning. The relative absorptive capacity measures are also shown to have greater explanatory power than the established measure of absorptive capacity, R&D spending. © 1998 John Wiley & Sons, Ltd.

Relative absorptive capacity and interorganizational learning

Over the last 50 years, there has been a remarkable convergence in the occupational distribution between white men, women, and blacks. We measure the macroeconomic consequences of this convergence through the prism of a Roy model of occupational choice in which women and blacks face frictions in the labor market and in the accumulation of human capital. The changing frictions implied by the observed occupational convergence account for 15 to 20 percent of growth in aggregate output per worker since 1960.

The Allocation of Talent and U.S. Economic Growth

Why do living standards differ so much across countries? A consensus in the development literature is that differences in productivity are a dominant source of these differences. But what accounts for productivity differences across countries? One explanation is that frontier technologies and best practice methods are slow to diffuse to low-income countries. The recent literature on misallocation offers a distinct but complementary explanation: low-income countries are not as effective in allocating their factors of production to their most efficient use. We provide our perspective on three key questions. First, how important is misallocation? Second, what are the causes of misallocation? And third, beyond the direct cost of lower contemporaneous output, are there additional costs associated with misallocation? A summary of our answers is as follows: Misallocation appears to be a substantial channel in accounting for productivity differences across countries, but the measured magnitude of the eff...

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The Causes and Costs of Misallocation

We contrast the intergenerational mobility rates of the historically disadvantaged scheduled castes and tribes (SC/ST) in India with the rest of the workforce in terms of their education attainment, occupation choices and wages. Using survey data from successive rounds of the National Sample Survey between 1983 and 2005, we find that intergenerational education and income mobility rates of SC/STs have converged to non-SC/ST levels during this period. Moreover, SC/STs have matched non-SC/STs in occupation mobility rates. We conclude that the last 20 years of structural changes in India have coincided with a breaking down of caste-based barriers to socioeconomic mobility.

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Breaking the Caste Barrier Intergenerational Mobility in India

Can large macroeconomic changes also alter the historical economic mobility patterns of various social groups? We examine this question by contrasting the fortunes of the historically disadvantaged scheduled castes and tribes (SC/ST) in India with the rest of the workforce in terms of their education attainment, occupation choices and wages. We study the period 19832005 using household survey data from successive rounds of the National Sample Survey. Our key …ndings are that wages have been converging across the two groups with rising education attainments accounting for the majority of this convergence. SC/STs have also been switching occupations at increasing rates during this period. Moreover, inter-generational education and income mobility rates of SC/STs have converged to non-SC/ST levels. Clearly, the last twenty years of major structural changes in India have seen a sharp improvement in the relative economic fortunes of these historically disadvantaged social groups. In fact, the median wages of SC/STs relative to non-SC/STs in India have surpassed the median wages of blacks relative to whites in the USA.

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Castes and Labor Mobility

Amongst the various inequities typically associated with the caste system in India, probably one of the most debilitating is the perception that one is doomed by birth, i.e., social and economic mobility across generations is di¢ cult. We study the extent and evolution of this lack of mobility by contrasting the intergenerational mobility rates of the historically disadvantaged scheduled castes and tribes (SC/ST) in India with the rest of the workforce in terms of their education attainment, occupation choices and wages. Using household survey data from successive rounds of the National Sample Survey between 1983 and 2005, we …nd that inter-generational education and income mobility rates of SC/STs have converged to non-SC/ST levels during this period. Moreover, SC/STs have been switching occupations relative to their parents at increasing rates, matching the corresponding switch rates of non-SC/STs in the process. Interestingly, we have found that a common feature for both SC/STs and non-SC/STs is that the sharpest changes in intergenerational income mobility has been for middle income households. This is

Breaking the Caste Barrier: Intergenerational Mobility

We develop a machine learning based tool for accurate prediction of development and socio-economic indicators from high resolution day-time satellite imagery. The indicators that we use are derived from the Census 2011 [The Ministry of Home Affairs, Government of India, 2011] and the NFHS-4 [The Ministry of Health and Family Welfare, Government of India, 2016] survey data. We use a deep convolutional neural network to build a model for regression of asset indicators from satellite images. We show that the direct regression of asset indicators gives superior R2 scores compared to that of transfer learning through night light data, which is a popular proxy for economic development used world wide. We also use the asset prediction model for accurate transfer learning of other socio-economic and health indicators which are not intuitively related to observable features in satellite images, or are not always well correlated with each other. The tool can be extended to monitor the progress of development of a region over time, and to flag potential anomalies because of dissimilar outcomes due to different policy interventions in a geographic region by detecting sharp spatial discontinuities in the regression output.

On monitoring development using high resolution satellite images.

We develop a machine learning based tool for accurate prediction of socio-economic indicators from daytime satellite imagery. The diverse set of indicators are often not intuitively related to observable features in satellite images, and are not even always well correlated with each other. Our predictive tool is more accurate than using night light as a proxy, and can be used to predict missing data, smooth out noise in surveys, monitor development progress of a region, and flag potential anomalies. Finally, we use predicted variables to do robustness analysis of a regression study of high rate of stunting in India.

Sourabh Paul

Papers

Breaking the Caste Barrier Intergenerational Mobility in India

Castes and Labor Mobility

Breaking the Caste Barrier: Intergenerational Mobility

On monitoring development using high resolution satellite images.

On monitoring development indicators using high resolution satellite images